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Tampere Wireless Research Center (TWRC)

Tag: Positioning

Bo Sun: From connectivity to awareness: Enabling sub‑meter to sub‑centimeter positioning with 5G/6G networks

In his doctoral dissertation, Bo Sun studied how future mobile networks (5G and beyond) can be used not only for communication but also for precise positioning and environmental sensing. The research shows that standard 5G signals can achieve sub-meter positioning and even create maps of surroundings, while new techniques using reconfigurable intelligent surfaces can improve accuracy to centimeter or sub-centimeter levels. These results are important because they allow reliable positioning in places where GPS does not work, such as indoors or in dense urban areas. The findings can benefit industries such as transportation, manufacturing, and public safety by enabling autonomous systems, smarter infrastructure, and cost-efficient monitoring using existing mobile networks.

Maija Mäkelä: New cooperative positioning methods enable localization in the absence of satellite signals

Satellite-based positioning cannot be taken for granted anymore – how to locate rescuers when signals vanish? M.Sc. (Tech.) Maija Mäkelä demonstrates in her dissertation novel cooperative positioning methods, that combine sensor information and distance measurements. This results in a satellite-independent positioning solution, which enables tracking of teams of pedestrians also under challenging conditions.

Roman Klus: Revolutionizing location-awareness in wireless networks with deep learning

For his doctoral dissertation, M.Sc. Roman Klus introduced a number of deep learning models to improve the localization and location-awareness capabilities within the current and future wireless networks, while focusing on challenges such as non-line-of-sight, network uncertainty, or data scarcity. The proposed solutions ensure localization accuracy and reliability, as well as support other network functions relying on knowledge of the user position, for example mobility management.

Elizaveta Rastorgueva-Foi: Facilitating precise positioning and environmental mapping in the millimeter-wave communication networks

In her doctoral dissertation, MSc (Tech) Elizaveta Rastorgueva-Foi studies how 5G and beyond networks can be used not only for communication, but also for high-accuracy positioning and real-time environmental sensing. She proposes new methods that help the network to collaborate with the connected devices to acquire and track their accurate locations, as well as to help mapping their surroundings – crucial steps towards autonomous driving, smart cities, and advanced robotics.

Lucie Klus: Boosting wearable performance with lossy compressions

Nowadays, wearable devices are ever-present in modern society, improving everyday life with intelligent functions and services. Their performance is limited by their size and battery, making energy efficiency one of the most relevant aspects of the system. In her doctoral dissertation M.Sc. Lucie Klus focuses on boosting the energy efficiency of the Internet of Things and wearable devices by implementing lossy compression techniques onto sensor-based time-series data and into indoor localization paradigms.

Mike Koivisto: DoA and ToA Estimation, Device Positioning and Network Synchronization in 5G New Radio - Algorithms and Performance Analysis

[FI] - Nopeasti yleistyvät 5G-verkot mahdollistavat käyttäjälleen entistä nopeamman tietoliikenneyhteyden. Samalla niissä käytettävä teknologia luo varteenotettavan ympäristön tehokkaaseen ja tarkkaan laitepaikannukseen myös satelliittipaikannuksen kannalta haastavissa ympäristöissä. Väitöskirjassaan DI Mike Koivisto tutki ja kehitti tehokkaita paikannusalgoritmeja, jotka mahdollistavat reaaliaikaisen ja erittäin tarkan laitepaikannuksen 5G-verkkojen radiosignaaleja käyttäen.